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Tier-1 brand and metro location increase competition, but senior niche role reduces applicant density.
Role requires deep, specialized ML/AI, LLM and MLOps expertise, limiting cross-industry transferability.
Explicit 12+ years plus senior AI, MLOps, RAG, and leadership requirements enforce strict shortlisting.
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Lead definition and scaling of enterprise AI engineering practices including reference architectures and best practices.
Design and develop core AI frameworks, prototypes, and reference implementations, focusing on advanced Retrieval-Augmented Generation (RAG) and multi-agent AI systems.
Architect and implement enterprise-grade AI evaluation frameworks for continuous performance, accuracy, safety, and cost assessment at scale.
12+ years in software engineering with 5-7 years in senior, hands-on AI/ML roles.
Expertise in designing, building, and deploying large-scale AI systems, including RAG pipelines and agentic AI ecosystems (e.g., LangChain, LlamaIndex).
Strong programming skills in Python and familiarity with AI/ML libraries (PyTorch, Hugging Face), cloud platforms (AWS, Azure, GCP), and LLMOps/MLOps.
Bachelor’s degree in Computer Science, Engineering, or related quantitative field (Master’s or PhD strongly preferred).
Senior-level technical leader with deep hands-on experience in building and scaling AI systems including AI evaluation at industrial scale.
Strong practitioner comfortable with complex technical problem-solving and delivering pragmatic, scalable AI solutions in a large organization.
Skilled mentor and communicator able to guide teams and evangelize AI engineering best practices across diverse stakeholders.